Rotavirus is the leading cause of severe diarrhea in children, and a major source of morbidity and mortality in developing countries. Vaccination has proven to be a safe and effective means of controlling the burden of rotavirus-associated gastroenteritis in developed countries, but logistical constraints and concerns over the reduced efficacy of the vaccines in developing country settings have hindered their wider adoption. Better evidence is needed to support the expected impact of vaccination in developing countries to overcome the barriers to vaccine introduction. We seek to address these concerns using a combination of statistical and mathematical modeling to gain a better understanding of the factors affecting the direct and indirect effects of rotavirus vaccination in developing countries. First, we will reanalyze data from pivotal birth cohort studies conducted in Mexico and India to explore the hypothesis that higher rates of rotavirus transmission and the younger age at infection in India compared to Mexico may help to explain the differences in protection from natural infection in these settings. Second, we will use mathematical models to examine the important drivers of rotavirus transmission dynamics in Bangladesh, Malawi, and Ghana. We will use the models to predict the impact of rotavirus vaccination in these settings accounting for both the direct and indirect effects of vaccination. Finally, we will validate and refine model predictions by comparing to data collected as part of ongoing studies of the impact of vaccination in Blantyre, Malawi and Accra and Navrongo, Ghana. These projects will improve our understanding of how the underlying transmission dynamics of rotavirus affect the expected direct and indirect effects of vaccination in developing countries, and will provide a validated platform for extending the modeling analyses to other countries to provide evidence-based support for rotavirus vaccine introduction.